Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Prefer not to say 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Prefer not to say
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports;Do arts and crafts;Exercise;Listen to hiphop and rap;Listen to rock/indie music;Use social media;Go to museums and galleries;Attend football matches;Other (Please specify) Game, go to the cinema
Devices used daily: Smartphone;Tablet;Other Desktop
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini;Perplexity;Microsoft Bing AI;Other Deepseek
LLM use cases: Translation;Brainstorming;Paraphrasing or finding synonyms;Solving math or logical problems;Analyze data;Generate art;Learning (e.g., explaining complex concepts in simple terms);Get information about current events;Answering questions about general knowledge;Collecting references;Summarizing long texts 
Contexts of LLM use: Entertainment;Learning;Personal;Creative or artistic 
Prompt 1: Can you analyze websites?
Prompt 2: Analyze an article's content.
Prompt 4: What does sdk in this context mean?
Prompt 5: If an sdk is used by developers to create apps, how does embedding a software development kit itself collect data or is sdk the wrong term?
Prompt 6: Why wouldn’t the code in this context be an api? If an sdk is a toolkit and is used by developers to create apps, why are they embedding it in the software? Couldn’t an attacker utilize the constructive nature of an sdk to manipulate an app as an attack vector?
Prompt 7: I would love that.
Prompt 8: If the companies in this article had used sandboxing techniques could they have avoided the compromising data collection by Amazon?
Prompt 9: No, thank you. Could you tell me more the side channel attacks you mentioned and how that data is utilized?
Prompt 10: Why doesn't restricting an SDK's wifi permission stop it from gaining access to network wifi information?
Comments: I don't know where to start here. AI is still in its early stages and people are both optimistic and fearful about its potential. People are both frustrated with AI's inaccuracies and the fact that it doesn't seem to know everything from the onset of its existence. While also being fearful of its all-knowing, all-seeing Skynet people replacing, famine causing future. It all really doesn't make a whole lot of sense to me because those fears are often overblown. Especially when those in the media, that have no background in anything technological start fearmongering. It harkens back to when the Today show hosts were musing to each other "have you heard of this internet?" Ai is a tool, currently it is very helpful to me and will become more helpful in the future. It makes learning easier and more streamlined. It gives me information and places to look further to understanding the topics that I am interested in. I understand Ai's potential and have to parse the bullshit coming from people that are all shouting into the void about its negative consequences. I have to figure out which of those voices aren't just imbeciles barking nonsense and which of those are genuine inevitabilities. Nonetheless, AI is here to stay, and I will be utilizing it to the best I can. You either have to adapt to and understand the technology that controls our lives otherwise you are at a disadvantage.